| Symptom | Cause | Fix |
|---|---|---|
nvcc: command not found | CUDA toolkit not in PATH | Add CUDA toolkit to PATH: export PATH=/usr/local/cuda/bin:$PATH |
pip install uv permission denied | System-level pip restrictions | Use pip3 install --user uv and update PATH |
| GPU not detected in training | CUDA driver/runtime mismatch | Verify driver compatibility: nvidia-smi and reinstall CUDA if needed |
| Out of memory during training | Model too large for available GPU memory | Reduce batch size, enable gradient checkpointing, or use model parallelism |
| ARM64 package compatibility issues | Package not available for ARM architecture | Use source installation or build from source with ARM64 flags |
| Cannot access gated repo for URL | Certain HuggingFace models have restricted access | Regenerate your HuggingFace token; and request access to the gated model on your web browser |
NOTE
DGX Spark uses a Unified Memory Architecture (UMA), which enables dynamic memory sharing between the GPU and CPU. With many applications still updating to take advantage of UMA, you may encounter memory issues even when within the memory capacity of DGX Spark. If that happens, manually flush the buffer cache with:
sudo sh -c 'sync; echo 3 > /proc/sys/vm/drop_caches'